Method and system for compiling competitive advertiser and keyword information for search engine advertisers

ABSTRACT

The present invention relates to a computer implemented method of generating a relevant COMPETITORS list in response to a search inquiry, the method comprising a number of steps such as receiving a search inquiry from a client having a client domain having a plurality of client domain keywords; performing a search of a computer network for data satisfying a set of search parameters; obtaining a first set of SERP&#39;s, said first set of SERP&#39;s containing a list of competitors domains and associated competitors domain keywords. This date then forms the basis of further calculations of “Inwards Overlap” and “Outwards Over-lap” to then calculate a competitor relevance score being the higher of the Inwards Overlap (as a percentage), and the Outwards Overlap (as a percentage).

FIELD OF THE INVENTION

This invention relates to keyword searching and ranking ofinformation/data.

There are many search engines currently in use that aim to provide a setof results or set of data specific to user's needs or parameters. Searchengines allow persons to search and display web pages of interest inaccordance with a defined set of keywords or keyword combinations.Search engines typically provide 2 types of results listings—naturallistings, and sponsored (paid) listings.

To generate natural listings, search engines “crawl” the web, harvestingweb pages and storing these in massive databases. When users make anenquiry the search engine scans it's database for pages that contain thesame keywords or keyword combinations, and ranks the harvested pagesaccording to a specific set of relevancy algorithms or user requirements

An example of this is the Google search engine in which the searchengine calculates a relevance score that tries to determine how closethe harvested pages is to the users requirements (Google PageRank). Theresults are then displayed to the user in an order based on thecalculated score.

The activity of optimising a web-site's web-pages in order to increasethe likelihood that a search engine ranks those pages highly within itsnatural results listings is called Search Engine Optimisation, or SEO.In the field of SEO competition for certain keywords is fierce and goodperformance on certain keywords may dramatically affect a company'smarket position.

Companies advertising their goods/services via a search engine'sSponsored Listings typically select a set of keywords relevant to theirproduct/service and set a budget in relation to those keywords and thendetermine the price for each selected keyword. When a company's ad isdisplayed the company pays the search engine when a potential consumerclicks on the ad. Search engines conduct auctions based on the bidsreceived by competitors on certain keywords. This then determines boththe position and placement of the ads on search results page. Keywordsthen become a valuable commodity. This activity is called PPC(pay-per-click) advertising.

It is often desirable for some companies to determine the keywords thattheir competitors consider important so as to help shape their marketingstrategy and in some cases also help to determine those companies thatare operating in the same keyword space that may in fact be unidentifiedcompetitors.

What we have now invented is an automated process and associatedmethodologies to provide effective identification of relevantcompetitors and relevant keywords for any specific Client Domain, byharvesting and analysing listings within Search Engine Results Pages(SERPS) that provides advantages over what is presently known allowingthe provision of automatic identification of relevant competitors andkeywords; automatic monitoring and reporting on competitor activity;automatic calculation and monitoring of competitors' share of voicewithin the set of relevant keywords; benchmarking and other purposes;assistance in campaign improvement, through identification of missing orpoor performing relevant keywords for that domain.

OBJECT OF THE INVENTION

It is an object of the present invention to provide a process andmethodologies for effective identification of Relevant Competitors andRelevant Keywords that will substantially overcome the drawbacks of thecurrently known methods.

Other objects and advantages of the present invention will becomeapparent from the following description, taking in connection with theaccompanying drawings, wherein, by way of illustration and example, anembodiment of the present invention is disclosed.

SUMMARY OF THE INVENTION

The term “keyword” may include one or more terms that can be used aspart of a query and may encompass more than a single word, or a phrase.

The term “relevant keyword” refers to any keyword which is likely to beuseful in generating traffic for the Client Domain, and which thereforeshould be considered in any monitoring or reporting of their searchengine marketing performance.

The term “SERP” refers to Search Engine Results Pages.

The term “relevant competitor” refers to any advertiser which a clientdomain would consider competes with them in the real world, and which itwould therefore expect to see considered in any monitoring or reportingof their search engine marketing performance.

The term “Competitor Relevance Score”, refers to the higher of theInwards Overlap (as a percentage), and the Outwards Overlap (as apercentage), so that users can rank the relevant competitors found, andreview Competitors with a low score.

According to the present invention, although this should not be seen aslimiting the invention in any way, there is provided a computerimplemented method of generating a relevant COMPETITORS list in responseto a search inquiry, the method comprising the steps of:

-   -   receiving a search inquiry from a client having a client domain        having a plurality of client domain keywords;    -   performing a search of a computer network for data satisfying a        set of search parameters;    -   obtaining a first set of SERP's, said first set of SERP's        containing a list of competitors domains and associated        competitors domain keywords;    -   calculating an “Inwards Overlap” being the proportion of the        client domain keywords that feature in the competitors domain        keywords;    -   calculating an “Outwards Overlap” being the proportion of the        competitors domain keywords that feature in the client domain        keywords;    -   calculating a competitor relevance score being the higher of the        Inwards Overlap (as a percentage), and the Outwards Overlap (as        a percentage);    -   ranking the competitors domains based on the competitor        relevance score.

In preference, the set of keywords is limited to sponsored listings.

In preference, the set of keywords is limited to natural listings.

In preference, the method further includes a minimum competitorrelevance score as set by a user, wherein any competitor relevance scorebeing less than the minimum competitor relevance results in thecompetitor being determined a non-relevant competitor.

According to the present invention, although this should not be seen aslimiting the invention in any way, there is also provided a computerimplemented method of generating a relevant KEYWORDS list in response toa search inquiry, the method comprising the steps of:

-   -   Compiling a database of associated competitors domain keywords        from the SERP's;    -   Determining which competitors use which keywords present in the        database of associated competitors domain keywords;    -   Calculate a keyword relevance score based on at least one of the        following:        -   The number of relevant competitors using a selected keyword;        -   Outwards overlap against each competitor using the keywords;        -   Number of competitors (relevant or non-relevant) using the            keywords;    -   Determine a list of relevant keywords from the database of        associated competitors domain keywords, based on the keyword        relevance score.

In preference, usage of a keyword by an associated competitor isconsidered as a vote that the keyword is also relevant to the ClientDomain

In preference, each vote has a credibility score=(Outward Overlap)³.

In preference, multiple votes for the same keyword used by a number ofassociated competitors can be combined to give a Combined Credibilityvote using the formula:

Combined Credibility of n votes=1−(1−V1)*(1−V2)* . . . *(1−Vn)

In preference, the Combined Credibility of n votes=Keyword RelevanceScore.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to understand the invention and to see how it may be carriedout in practice, an embodiment will now be described, by way of anon-limiting example only, with reference to the accompanying drawing inwhich:

BRIEF DESCRIPTION OF THE INVENTION

By way of example, an embodiment, which is a non-limiting example, ofthe invention is described more fully hereinafter with reference to theaccompanying drawings, in which:

FIG. 1 shows an schematic overview of the present invention.

If an Advertiser appears within the SERPs on a particular keyword, andthe Client Domain also appears within the SERPS for that same keyword,then that Advertiser and the Client Domain can be considered to becompeting for traffic on that particular keyword.

However, advertising for traffic on the same keyword does notautomatically mean that the Advertisers in question are necessarily“competitors” in the normal sense of the word, as they may be offeringcompletely different services.

For example, one advertiser on the keyword phrase “Paris France” may beoffering hotel bookings in Paris; whilst a second could be offeringflights to Paris; and a third offering tickets to the Rugby World Cupfinals in Paris France. So, whilst the hotel, airline and rugbyassociation sites are all advertising on this same keyword, they are infact not “real world” competitors.

Fortunately the situation does become clearer when considering multiplekeywords. Advertisers typically appear in the SERPS for thousands, oreven tens of thousands of keywords, which we will call each Advertiser's“Keyword Set”. If a particular advertiser is found to be competing fortraffic on a large number of the same keywords as the Client Domain,then it is likely that that advertiser is offering similar products andservices as the Client Domain, and is in fact a “Competitor” in thenormal sense of the word.

Referring again to the example above:

hotel sites are likely to appear on hundreds of hotel name keywords incommon with other hotel sites;

flights websites are likely to have thousands of flights relatedkeywords in common with each other, and the rugby association site isnot likely to have any of the above keywords in common with the othersites.

When considering the overlap between each Advertiser's Keyword Set, andthe Client Domain's own Keyword Set, it is useful to consider both the:

“Inwards Overlap”—being the proportion of the Client Domain's keywordsthat are also within the other advertiser's Keyword Set; and

“Outwards Overlap”—being the proportion of the other advertiserskeywords that are used by the Client Domain, and so within the ClientDomain's Keyword Set

Advertisers can be divided into the following 4 categories:

Direct Competitor, Super Competitor, Niche Competitor and Non Competitor

Outwards Overlap: HIGH Outwards Overlap: LOW Inwards DIRECT COMPETITOR:SUPER COMPETITOR: Overlap: The other advertiser has most (or all) of Theother advertiser has most (or HIGH the Client Domain's keywords, and theall) of the Client Domain's Client Domain has most (or all) of thekeywords, but the Client Domain other advertiser's keywords. only has asmall proportion of the This means the other advertiser and the otheradvertiser's keywords. Client Domain have very similar This means theother advertiser Keyword Sets. has many more keywords than the Both theClient Domain and the other Client Domain, and whilst offeringAdvertiser are DIRECT most (or all) of the products and COMPETITORS ofeach other. services of the Client Domain, it also offers many moreproducts. The other advertiser is a SUPER COMPETITOR of the ClientDomain, whilst the Client Domain is a NICHE COMPETITOR of the otheradvertiser. Inwards NICHE COMPETITOR: NON COMPETITOR: Overlap: TheClient Domain has most (or all) of The Client Domain has only a few LOWthe other advertiser's keywords, but the (or none) of the otheradvertiser's other advertiser only has a small keywords, and the otheradvertiser proportion of the Client Domain's has only a few (or none) ofthe keywords. Client Domain's keywords. This means the Client Domain hasThis means the other advertiser many more keywords than the other andthe Client Domain have very advertisers, and whilst offering most (ordifferent Keyword Sets. Whilst there all) of the products and servicesof the might be some keywords in other advertiser, it also offers manycommon, it is likely that they are more products. offering differentproducts and The other advertiser is a NICHE services on these fewkeywords. COMPETITOR of the Client Domain, Even if they are offering thesame whilst the Client Domain is a SUPER products and services, the veryCOMPETITOR of the other advertiser. small overlap in their businessmodels means they are not likely to consider each other as relevantcompetitors.

In order to implement a minimum Competitor Relevance Score, below whichany advertiser is considered not to be a Relevant Competitor, andthereafter automatically excluded from any reporting or monitoringperformed by the system

Allow users to override the automatic status assignment for someadvertisers, and rather manually specify those advertisers as “RelevantCompetitors” or “Non-Competitors” regardless of their computed score.

Allow users to specify a set of “Known Relevant Terms” to be deemed tobe included in the Client Domain's Keyword Set when determining overlapwith other advertisers Keyword Sets, regardless of whether the ClientDomain has actually appeared on these terms in the SERPS. This is usefulwhen a Client Domain has not yet appeared in any SERPS pages, but stillwishes to start monitoring their competitive landscape.

Keep a record of each Advertiser's Outwards Overlap to assist inderivation of Relevant Keywords—see below.

In some circumstances, it may also be useful to:

Limit the determination of Keyword Sets to only Sponsored Listings orNatural Listings.

Consider the sum of the traffic available on the overlapping termsbetween each advertiser and the Client Domain (called the CompetedClicks) in determining the Competitor Relevance Score. The higher thenumber of Competed Clicks, the more likely that an advertiser is arelevant competitor. Put another way, an advertiser competing on only asmall number of high traffic terms is perhaps more likely to beconsidered a competitor than another advertiser competing on a largenumber of very low traffic terms.

Competitor Relevance Score=higher of the “Inwards Overlap (as apercentage)” and the “Outwards Overlap” (as a percentage)  Formula

Part 2: Relevant Keywords

What is a relevant Keyword?

A relevant Keyword is any keyword which is likely to be useful ingenerating traffic for the Client Domain, and which therefore should beconsidered in any monitoring or reporting of their search enginemarketing performance.

In order to reliably identify Relevant Keywords based on SERPS listings,one needs to be able to

-   -   Implement a process to continually grow the keyword database,        gathering more and more keywords which are at least likely to be        relevant. Ideally this should be automated.    -   Harvest the SERPS pages for these keywords, recording which        keywords each advertiser uses (the Advertiser's Keyword Set),        and conversely which advertisers appear on each keyword;    -   And then crucially, implementing a methodology and process to        extract from this raw data, the set of keywords which are in        fact relevant to the Client Domain

Step 3: Determining Relevant Keywords

Relevant Keywords are derived from the keyword sets of the RelevantCompetitors. Importantly, not all the keywords of relevant competitorsare necessarily relevant to the Client Domain, as some RelevantCompetitors may offer additional products and services which are notoffered by the Client Domain.

Determining Relevant Keywords is a 2 step process.

First compute a “Keyword Relevance Score”

Then select Relevant Keywords based on the Keyword Relevance Score, andother factors.

The key indicators useful in determining the raw Keyword Relevance Scoreare:

A. The number of Relevant Competitors using the keyword (morecompetitors using the term gives us more confidence)

B. Outwards Overlap against each Competitor using that keyword (higheroutwards overlap suggests the terms come from a more highly correlatedkeyword set)

Number of competitors using the keyword: The higher the number ofRelevant Competitors using a keyword, the more likely it is that thekeyword is relevant to the Client Domain.

Outwards overlap: “Outwards Overlap” is important when:

We expect that any keyword used by a Direct Competitor (these have aHIGH outwards overlap) is very likely to be highly relevant keyword forthe Client Domain too, since there is already such a high correlationbetween the Keyword Sets.

Similarly, if a Niche Competitor (also having a HIGH outwards overlap)has a keyword which the Client Domain does not have, then it too islikely to be relevant to the Client Domain. This is because the ClientDomain already has most of that advertiser's other keywords, and webelieve the other advertiser is most likely offering a subset of theClient Domain's own products and services. Any additional keywords theyare appearing on are therefore also likely to be relevant to the ClientDomain too.

In contrast to this, Super Competitors (which have a LOW outwardsoverlap) will have many keywords which the Client Domain does not have,and there is a good chance these keywords may relate to products andservices which the Client Domain does not offer, and (although they maybe) these are not necessarily Relevant Keywords.

Looking at the above, it can be seen that the “Outwards Overlap”calculated for each Relevant Competitor can be usefully used as ameasure of confidence that each Competitor's keyword may be relevant tothe Client Domain.

Stated another way, the “Outwards Overlap” reflects the Competitor'scredibility when it comes to suggesting relevant keywords for the ClientDomain, or the probability that its own keywords are likely to berelevant to the Client Domain.

Keyword Relevance Score

The presence of a keyword in each Relevant Competitor's Keyword Set canthen been seen as an independent “vote” that that keyword is also aRelevant Keyword for the Client Domain, and further to consider that thecredibility of each vote (which might also be described as theprobability of the vote being correct) can be based on the “OutwardsOverlap” (0%-100%) of the voter (i.e. the Competitor).

A person skilled in the art would then understand this and be able tomake use of alternative ways to capture these factors withoutnecessarily deviating from the scope of the invention

When translating the “Outwards Overlap” of Competitor A into a measureof credibility (or assumed probability that each of Competitor A'skeywords are equally relevant to the Client Domain), by using the cube(the third power of a number) of the Outwards Overlap gives results.

Credibility (probability keyword is relevant)=(Outward Overlap)³

This translates into real world examples as follows:

-   -   If the Client Domain already shares 9,999 of 10,000 keywords        used by a competitor (99.99% Outwards Overlap), then we are        assuming that there is a 0.9999³=99.97% probability that the        remaining keyword is also relevant to the Client Domain.    -   If the Client Domain already shares only 5,000 of 10,000        keywords used by a competitor (50% Outwards Overlap), then we        are assuming that there is only a 0.5³=12.5% probability that        each of the other 5000 keywords are also relevant to the Client        Domain. Without additional “votes” from other competitors, these        keywords are unlikely to pass the threshold to be considered        relevant.

The next consideration is how to combine multiple “votes” from 2 or moredifferent Competitors for the same keyword.

Again, the person skilled in the art would understand that they couldapply this in a number of ways without deviating from the scope of theinvention; the concept is that each vote removes a portion of theremaining uncertainty left after considering the earlier votes. And thatthe amount of uncertainty removed by each vote is based on thecredibility of that vote.

For example, a vote for Keyword K1 by Competitor A with credibility 40%would mean we are 40% certain that the keyword K1 is relevant to theClient Domain. The remaining uncertainty is 60%.

A second vote for the same Keyword K1, by a different Competitor B withcredibility 50%, would remove 50% of the 60% remaining uncertainty,increasing the overall certainty that K1 is relevant from 40% to 70%overall.

This can be stated as:

$\begin{matrix}{\begin{matrix}{{Combined}\mspace{14mu} {Credibility}} \\{{of}\mspace{14mu} 2\mspace{14mu} {votes}}\end{matrix} = {{V\; 1} + {\left( {1 - {V\; 1}} \right)*V\; 2}}} \\{= {{V\; 1} + {V\; 2} - {V\; {1 \cdot V}\; 2}}} \\{= {1 - {\left( {1 - {V\; 1}} \right)*\left( {1 - {V\; 2}} \right)}}}\end{matrix}$

This formula can be written more generically to consider n votes. If wewrite Vk for the credibility of Vote k, we have:

Combined Credibility of n votes=1−(1−V1)*(1−V2)* . . . *(1−Vn)

This formula is the same as saying

$\begin{matrix}{\begin{matrix}{{Combined}\mspace{14mu} {Credibility}} \\{{of}\mspace{14mu} n\mspace{14mu} {votes}}\end{matrix} = {1 - {\left( {{Probability}\mspace{14mu} {Vote}\mspace{14mu} 1\mspace{14mu} {is}\mspace{14mu} {Wrong}} \right)*}}} \\{{\left( {{Probability}\mspace{14mu} {Vote}\mspace{14mu} 2\mspace{14mu} {is}\mspace{14mu} {Wro}\; {ng}} \right)*\ldots*}} \\{\left( {{Prob}\mspace{14mu} {Vote}\mspace{14mu} k\mspace{14mu} {is}\mspace{14mu} {Wrong}} \right)}\end{matrix}$

Which is also the same as saying “1−(probability all the independentvoters are wrong)”, which is intuitively also correct.

Keyword Relevance Score=Combined Credibility of all Votes for thatKeyword

When computing this score within a typical Database application, it ishelpful to express the formula using logarithms, so that the formula canbe based on an arithmetic SUM (very efficient in database applications)of a variable number of votes, rather than the PRODUCT of a number ofdifferent terms.

$\begin{matrix}{\begin{matrix}{{Keyword}\mspace{14mu} {Relevance}} \\{Score}\end{matrix} = {1 - {\left( {1 - {V\; 1}} \right)*\left( {1 - {V\; 2}} \right)*\ldots*\left( {1 - {Vn}} \right)}}} \\{= {1 - {\exp \left( {{SUM}\left( {\log \left( {1 - {Vk}} \right)} \right)} \right)}}}\end{matrix}$

As can now be readily appreciated, the disclosed method allowsautomation of the above process is very important, as it makes itcommercially viable to offer a tool to perform all of the followingtasks, with minimal human intervention or set-up that was until thispoint unknown. This method/process/systems described herein allows for:

Automatic identification of relevant competitors and keywords

Automatic monitoring and reporting on competitor activity

Automatic calculation and monitoring of competitors' share of voicewithin the set of relevant keywords, for benchmarking and other purposes

Assistance in Campaign Improvement, through identification of missing orpoor performing relevant keywords for that domain (rather thanirrelevant keyword suggestions)

Although the invention has been herein shown and described in what isconceived to be the most practical and preferred embodiment, it isrecognized that departures can be made within the scope of theinvention, which is not to be limited to the details described hereinbut it is to be accorded the full scope of the appended claims so as toembrace any and all equivalent devices, methods and apparatus.

Various modifications may be made in details of design and construction[and process steps, parameters of operation etc] without departing fromthe scope and ambit of the invention.

1. A computer implemented method of generating a relevant competitors list in response to a search inquiry, the method comprising the steps of: a. receiving a search inquiry from a client having a client domain having a plurality of client domain keywords; b. performing a search of a computer network for data satisfying a set of search parameters; c. obtaining a first set of Search Engine Results Pages, said first set of Search Engine Results Pages containing a list of competitors domains and associated competitors domain keywords; d. calculating an Inwards Overlap value being the proportion of the client domain keywords that feature in the competitors domain keywords; e. calculating an Outwards Overlap value being the proportion of the competitors domain keywords that feature in the client domain keywords; f. calculating a competitor relevance score being the higher of the Inwards Overlap as a percentage, and the Outwards Overlap as a percentage; and g. ranking the competitors domains based on the competitor relevance score.
 2. The method of claim 1, wherein the set of keywords is limited to sponsored listings.
 3. The method of claim 1, wherein the set of keywords is limited to natural listings.
 4. The method of claim 1, wherein the method further includes a minimum competitor relevance score set by a user, wherein any competitor relevance score being less than the minimum competitor relevance results in the competitor being determined a non relevant competitor.
 5. A computer implemented method of generating a relevant keywords list in response to a search inquiry, the method comprising the steps of: a. compiling a database of associated competitors domain keywords from Search Engine Results Pages; b. determining which competitors use which keywords present in the database of associated competitors keywords; c. calculate a keyword relevance score based on at least one of the following: i. the number of relevant competitors using a selected keyword; ii. outwards overlap against each competitor using the keywords; iii. number of relevant competitors or non-relevant competitors using the keywords; and d. determine a list of relevant keywords from the database of associated competitors domain keywords, based on the keyword relevance score.
 6. The method of claim 5, wherein usage of a keyword by an associated competitor is considered as a vote that the keyword is also relevant to a Client Domain.
 7. The method of claim 5, wherein each vote has a credibility score equal to Outward Overlap.
 8. The method of claim 5, wherein multiple votes for the same keyword used by a number of associated competitors can be combined to give a Combined Credibility vote using the formula: Combined Credibility of n votes=1−(1−V1)*(1−V2)* . . . *(1−Vn).
 9. The method of claim 5, wherein the Combined Credibility of n votes equals a Keyword Relevance Score.
 10. The method of claim 5, wherein the set of keywords is limited to sponsored listings or natural listings.
 11. The method of claim 5, wherein the set of keywords is limited to sponsored listings or natural listings, and wherein the method further includes a minimum competitor relevance score set by a user, wherein any competitor relevance score being less than the minimum competitor relevance results in the competitor being determined a non relevant competitor.
 12. The method of claim 5, wherein the set of keywords is limited to sponsored listings or natural listings, and wherein usage of a keyword by an associated competitor is considered as a vote that the keyword is also relevant to a Client Domain.
 13. The method of claim 5, wherein the set of keywords is limited to sponsored listings or natural listings, and wherein each vote has a credibility score equal to Outward Overlap.
 14. The method of claim 5, wherein the set of keywords is limited to sponsored listings or natural listings, and wherein multiple votes for the same keyword used by a number of associated competitors can be combined to give a Combined Credibility vote using the formula: Combined Credibility of n votes=1−(1−V1)*(1−V2)* . . . *(1−Vn).
 15. The method of claim 5, wherein the set of keywords is limited to sponsored listings or natural listings, and wherein the Combined Credibility of n votes equals a Keyword Relevance Score.
 16. A computer implemented method of generating a relevant competitors list in response to a search inquiry, the method comprising the steps of: a. receiving a search inquiry from a client having a client domain having a plurality of client domain keywords; b. performing a search of a computer network for data satisfying a set of search parameters; c. obtaining a first set of Search Engine Results Pages, said first set of Search Engine Results Pages containing a list of competitors domains and associated competitors domain keywords; d. calculating an Inwards Overlap value being the proportion of the client domain keywords that feature in the competitors domain keywords; e. calculating an Outwards Overlap value being the proportion of the competitors domain keywords that feature in the client domain keywords; f. calculating a competitor relevance score being the higher of the Inwards Overlap as a percentage, and the Outwards Overlap as a percentage; g. ranking the competitors domains based on the competitor relevance score; and wherein the set of keywords is limited to sponsored listings or natural listings.
 17. The method of claim 16, wherein the method further includes a minimum competitor relevance score set by a user, wherein any competitor relevance score being less than the minimum competitor relevance results in the competitor being determined a non relevant competitor.
 18. The method of claim 16, wherein usage of a keyword by an associated competitor is considered as a vote that the keyword is also relevant to a Client Domain.
 19. The method of claim 16, wherein each vote has a credibility score equal to Outward Overlap.
 20. The method of claim 16, wherein multiple votes for the same keyword used by a number of associated competitors can be combined to give a Combined Credibility vote using the formula: Combined Credibility of n votes=1−(1−V1)*(1−V2)* . . . *(1−Vn) wherein the Combined Credibility of n votes equals a Keyword Relevance Score. 